Kevin Squire is a PhD in Electrical Engineering and former Computer Science professor with a strong interest in bioinformatics and human genetics. To this end, he joined Dr. Stanley F. Nelson's laboratory as a Postdoctoral Fellow in Human Genetics at UCLA one year ago, in order to retrain in bioinformatics and sequencing. Kevin's background in machine learning gives him a good foundation for a career in bioinformatics. What he needs, and what obtaining this grant will give him, is a good background in basic biology, biochemistry, and genetics, in order to better understand the biological processes behind the data he is working with. Kevin explorations in genetics have inspired him to make his career in this field. He hopes to gain a much better understanding of biology in order to ask and answer research questions relevant to the biology of cancer using second (and later) generation sequencing and through the use and development of relevant tools and analysis. As part of the research development plan, Kevin will complete a didactic coursework component in the first 2 years, to fill in the gaps in biology and bioinformatics in his background. During and after that, his research will focus on giving him a better understanding the genetics of cancer, attempting to answer relevant research questions from high throughput genomic sequencing data, through the use and creation of sequence analysis tools and other bioinformatics tools. Through his coursework and research, Kevin will attain the necessary skills to become an independent researcher in bioinformatics and genetics. PUBLIC HEALTH RELEVANCE: Cancer is a genetic disease, caused by mutations in DNA and other genetic changes which affect how cells work. The work in this proposal uses and enhances new sequencing technology to help accurately determine exactly what changes are occurring in tumor DNA and RNA, which in turn affect protein production and the health of the cell. While much of the work is broadly applicable, the research will be evaluated in glioblastoma, the most common and most deadly form of brain cancer, and will help determine the best course of treatment for patients with this disease.